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The Digital Divide |
NEWS |
It’s no secret that the industrial and manufacturing industry is in the midst of a sea change. Industrial giants PTC and Siemens have spent well over US$1 billion on Industrial Internet of Things (IIoT)-related acquisitions; additive manufacturing funding has started to pop, with Carbon and Desktop Metal alone raising a total of more than US$1 billion; and distributed manufacturing has gotten smarter, with companies like 3D Hubs now able to automate 93% of digital workorders as discussed in the ABI Insight Cloud-Based Contract Manufacturing Gets New Money (IN-5438). While there is an incubation period following most of these developments (e.g,, PTC will not integrate the assets of its Frustum acquisition into its Creo product line until 1Q 2020, Carbon and Desktop Metal need time to hire staff and activate strategy), they represent meaningful advances to infrastructure—connectivity, application enablement, device management, PLM, etc.—that have been building over a number of years and are ready to come to fruition.
This ABI Insight examines the US$1 trillion digital factory market (by 2030) in the context of ABI Research’s Industry 4.0 Maturity Model, which provides a framework for industrial and manufacturing organizations to organize their digital transformation initiatives around where they want to be based on where they are today.
The Evolution of Automation |
IMPACT |
Most factories aren’t as flexible or configurable as the products they produce. This is a big challenge when it comes to automation, and an important one to solve when the ability to automate determines success. Historically, automation required significant capital investment, a substantial amount of time to deploy, and Systems Integrators (SIs) whose skill and ability determined the success or failure of such initiatives. These aspects were undesirable on their own, let alone together, but were endured because of the importance of automating repetitive tasks.
While it could be argued that the merit of automation has never been greater for manufacturing and industrial operations, there is no question that the way companies think about and approach the issue is of a different nature. Enter Industry 4.0 thinking and the idea that everything should be digitally-enabled and data driven. This means using software to automate repetitive tasks otherwise performed by humans, connecting edge and cloud infrastructure for asset- and item-level visibility, and mastering downtime interruption so you can focus less on past issues and more on current and future operations (uptime optimization). When you do this, the result is lower capital investment, faster deployment cycles, less reliance on SIs, greater flexibility and agility, and the ability to more easily replicate and scale. The challenge is finding the right technologies, tools, and deployment models that works for you and your organization.
Measuring Industry 4.0 Maturity |
RECOMMENDATIONS |
The following is a set of proven tips to help overcome some of the most common roadblocks based on the Industry 4.0 Maturity Model:
There is a wide and growing range of digitally enabled, data-driven solutions aimed directly at the industrial and manufacturing sector. Without the right understanding of these technologies—and how they fit together—it is impossible to know when to jump in, let alone where to go, what to do, and how to do it. ABI Research developed the Industry 4.0 Maturity Model to make this process easier.